Introduction to Uncertainty Quantification

Uncertainty quantification is a topic of increasing practical importance at the intersection of applied mathematics, statistics, computation, and numerous application areas in science and engineering. This text provides a framework in which the main objectives of the field of uncertainty quantificat...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Sullivan, T.J (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Colección:Texts in Applied Mathematics, 63
Temas:
Probabilities.
Mathematical optimization.
Numerical analysis.
Engineering mathematics.
Engineering-Data processing.
Mathematical physics.
Probability Theory.
Optimization.
Numerical Analysis.
Mathematical and Computational Engineering Applications.
Theoretical, Mathematical and Computational Physics.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Introduction
  • Measure and Probability Theory
  • Banach and Hilbert Spaces
  • Optimization Theory
  • Measures of Information and Uncertainty
  • Bayesian Inverse Problems
  • Filtering and Data Assimilation
  • Orthogonal Polynomials and Applications
  • Numerical Integration
  • Sensitivity Analysis and Model Reduction
  • Spectral Expansions
  • Stochastic Galerkin Methods
  • Non-Intrusive Methods
  • Distributional Uncertainty
  • References
  • Index.

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